Role Purpose
The Senior Fraud & Operational Risk Analyst is responsible for executing and strengthening first-line fraud and operational risk management across the bank/fintech. The role focuses on fraud risk identification, monitoring, analytics, investigations, remediation, and control enhancement across products, channels, systems, and customer journeys.
This position plays a critical role in protecting the organisation against fraud, financial crime, and operational losses while supporting regulatory compliance, business growth, and customer trust.
Key Responsibilities
Fraud Risk & Operational Risk Management (First Line)
- Identify, assess, and manage fraud and operational risk exposures across products, channels, systems, and processes.
- Maintain and enhance fraud risk assessments, risk and control matrices (RCMs), and fraud risk registers.
- Design, implement, and monitor preventive and detective fraud controls aligned to the organisation’s risk appetite.
- Act as a first-line risk partner to business, product, technology, and operations teams.
Fraud Monitoring & Detection
- Develop, manage, and optimise transaction monitoring rules, alerts, and fraud detection logic across core banking and digital platforms.
- Analyse fraud trends, typologies, root causes, and emerging risks.
- Review fraud alerts and support escalation, containment, and decision-making processes.
Data Analytics & Technology Enablement
- Use data analytics to identify anomalies, patterns, and fraud indicators.
- Write and optimise queries using SQL and support analytics using Python and/or Java.
- Contribute to the development and enhancement of AI and machine learning–based fraud models (rules-based, supervised and unsupervised).
- Partner with technology teams to enhance core banking systems, fraud engines, and monitoring platforms.
Investigations & Case Management
- Conduct and support fraud investigations, including transactional analysis, evidence gathering, and root cause analysis.
- Prepare investigation reports, loss assessments, and management summaries.
- Support recovery actions, internal disciplinary processes, and referrals to law enforcement where required.
Remediation & Control Enhancement
- Drive remediation actions following fraud incidents, control failures, audits, or regulatory reviews.
- Recommend and implement control improvements, system enhancements, and process changes.
- Track remediation actions to closure and report on effectiveness.
Reporting & Stakeholder Engagement
- Produce regular fraud risk, losses, trends, and KPI reporting for senior management and governance forums.
- Present insights, findings, and recommendations to stakeholders across risk, compliance, operations, and technology.
- Contribute to fraud risk strategy, policies, standards, and procedures.
Key Competencies & Skills
Technical & Analytical Skills
- Strong fraud risk and operational risk management capability.
- Advanced data analysis and problem-solving skills.
- Proficiency in:
- SQL
- Python
- Google Cloud Console
- Looker Studio
- PowerBi
- Azure
- Experience working with AI and Machine Learning concepts for fraud detection (model development, tuning, validation, or implementation).
- Strong understanding of transaction monitoring systems, fraud engines, and core banking platforms.
Risk & Fraud Expertise
- Deep understanding of fraud typologies (card fraud, digital fraud, account takeover, internal fraud, payments fraud, etc.).
- Experience designing and maintaining risk and control matrices (RCMs).
- Knowledge of banking and fintech operating models, products, and payment ecosystems.
Behavioural & Professional Skills
- Strong investigative mindset with high attention to detail.
- Ability to translate data and technical findings into clear business insights.
- Excellent stakeholder engagement and communication skills.
- Strong ownership, accountability, and ability to work independently.
- Ability to operate in fast-paced, agile, and evolving environments.
Qualifications & Experience
Minimum Requirements
- Bachelor’s degree in finance, Risk Management, Accounting, Information Systems, Data Science, or a related field.
- 3–5 years’ experience in fraud risk management, operational risk, financial crime, or analytics within a bank or fintech.
- Hands-on experience with fraud monitoring, investigations, analytics, and remediation.
Advantageous
- Postgraduate qualification or professional certification in Risk, Fraud, AML, or Data Analytics.
- Experience with fintech platforms, digital banking, or payments.
- Exposure to regulatory engagements, audits, or assurance reviews.
- Experience implementing or enhancing AI/ML-driven fraud solutions
Key Performance Indicators (KPIs)
- Reduction in fraud losses and repeat incidents.
- Effectiveness of fraud detection and monitoring controls.
- Timely closure of investigations and remediation actions.
- Quality of fraud risk assessments, RCMs, and reporting.
- Stakeholder satisfaction and audit/regulatory outcomes.